Solving the last mile delivery problem using iterated local search approach

Author(s):  
Zhongkai Cai ◽  
Zizhen Zhang ◽  
Huang He
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sayan Chakraborty ◽  
Kalpit Darbhe ◽  
Sarada Sarmah

Purpose In the modern era of e-grocery, attended home delivery (AHD) has been identified as a crucial part of the last-mile delivery problem. This paper aims to deal with a real-life last-mile-delivery problem in the context of the Indian public distribution system (PDS). The authors identified two different environments for the said AHD problem and proposed two different approaches to address the issue under these problem settings. Design/methodology/approach In this study, the authors first consider the problem in a static environment and propose an iterated local search (ILS) integrated with an adaptive large neighborhood search (ALNS) meta-heuristic algorithm to obtain a routing solution. Thereafter, they extend the study in a dynamic environment where new delivery requests occur dynamically and propose a heuristic algorithm to solve the problem. For the dynamic case, multiple scenarios for the occurrence of delivery requests are considered to determine decisions regarding the opportunity to include a new request into the current solution. Findings By computational experiments, the authors show that the proposed approach performs significantly well for large size problem instances. They demonstrate the differences and advantages of the dynamic problem setting through a set of different scenarios. Also, they present a comparative analysis to show the benefits of adopting the algorithm in dynamic routing scenarios. Research limitations/implications Future research may extend the scope of this study by incorporating stochastic delivery failure probabilities and customer behavior affecting the delivery response. Also, the present study does not take inventory policies at the depot into consideration. It will be of interest to see how the system performs under the uncertainty of supply from the depot. Despite the limitations, the authors believe that this study provides food for thought and encouragements for practitioners. Practical implications This study shows the benefits of adopting an AHD problem in a dynamic setting in terms of customer service as compared to a traditional static environment. The authors clearly demonstrate the differences and advantages of the dynamic problem setting through a set of different scenario analysis. Social implications This paper investigates a real-life AHD problem faced by the Department of Food, Supply and Consumer Affairs, India. The findings of this study will be of particular interest to the policy-makers to build a more robust PDS in India. Originality/value The study is unique and highly relevant for real-world applications and can help build a more robust AHD system. Also, the proposed solution approaches to aid the problem in both static and dynamic routing scenarios will be of particular interest to practitioners.


2012 ◽  
Vol 46 (17) ◽  
pp. 9481-9490 ◽  
Author(s):  
Kyo Suh ◽  
Timothy Smith ◽  
Michelle Linhoff

2021 ◽  
pp. 115894
Author(s):  
Li Jiang ◽  
Xiaoning Zang ◽  
Ibrahim I.Y. Alghoul ◽  
Xiang Fang ◽  
Junfeng Dong ◽  
...  

2017 ◽  
Author(s):  
◽  
Pengkun Zhou

Cooperation between a truck and a drone for last-mile delivery has been viewed as a way to help make more efficient ways of delivery of packages because of the great advantage of drones delivery. This problem was described and formulated a as FSTSP by Maurry and Chu. Because of the weakness concerning drones' batteries lifespan, this paper proposed a new delivery scenario in which a charge-station will be applied in the truck-drone delivery network to increase the performance of the last-mile delivery. This new delivery problem is formulated for the first time in this thesis as a multi-objective problem. The purpose of this is to address both transportation cost and total time consumption. Data analysis is conducted to explore the relation between factors and the overall objective. The analysis shows that a charge-station will significantly increase the performance of the last-mile delivery. Lastly, future work is discussed that will enhance the model even more and possibly lead to better ways to use drones for delivery.


2021 ◽  
Vol 18 ◽  
pp. 636-645
Author(s):  
Junyi Mo ◽  
Shunichi Ohmori

In the last decade, dynamic and pickup delivery problem with crowd sourcing has been focused on as a means of securing employment opportunities in the field of last mile delivery. However, only a few studies consider both the driver's refusal right and the buffering strategy. This paper aims at improving the performance involving both of the above. We propose a driver-task matching algorithm that complies with the delivery time constraints using multi-agent reinforcement learning. Numerical experiments on the model show that the proposed MARL method could be more effective than the FIFO and the RANK allocation methods


Sign in / Sign up

Export Citation Format

Share Document